隨著網際網路的發展和第三方平台的出現，供應鏈的發展也逐漸趨於多元化。不同於以往單一的傳統銷售管道，企業還可以通過多管道的銷售，例如增加以網路第三方平台做直接銷售的雙管道銷售，來提升收益。然而，由於供應鏈結構之複雜性，過往的相關研究中，對更貼近實際狀況的資本約束之雙管道供應鏈模式的討論和分析卻非常稀少。
為了求解更複雜且反映現實問題之供應鏈決策問題，本文章研究利用賽局理論概念以雙管道供應鏈中具有資金約束的製造商、零售商、第三方平台與貸款人之間的定價談判程式為主軸，代入Stackelberg模型理論將其供應鏈模型架構以階層式之多階層規劃數學模型做描述，針對不同融資方案定價問題，求解最佳的定價策略，以實現供應鏈之共同利益最大化。
本研究提出將改良群體演算法(improved Simplified Swarm Optimization, iSSO)應用於多階層規劃問題(Multi-level Programming Problem, MLPP)之多階層改良簡化群優化演算法（Multi-level Improved Simplified Swarm Optimization, MLiSSO）應用在此供應鏈的訂價決策問題模型上，並使用三個過往相關MLPP來實驗作為方法效果驗證。實驗結果表明，MLiSSO演算法具有求解有效性、品質以及穩定性，並可用於解決供應鏈模型之定價策略問題，此外，此算法亦能應用至其他MLPP上。

With the evolution of the Internet and the introduction of third-party platforms, a diversified supply chain has gradually emerged. In contrast to the traditional single sales channel, companies can also increase their revenue by selling through multiple channels, such as dual-channel sales: adding a sales channel for direct sales through online third-party platforms. However, due to the complexity of the supply chain structure, previous studies have rarely discussed and analyzed the capital-constrained dual-channel supply chain model which is more relevant to the actual situation.
To solve more complex and realistic supply chain decision problems, this paper uses the concept of game theory to describe the pricing negotiation procedures among the capital-constrained manufacturers and other parties in the dual-channel supply chain by applying the Stackelberg game theory to describe the supply chain structure as a hierarchical multi-level mathematical model to solve the optimal pricing strategy for different financing options to achieve the common benefit of the supply chain.
In this study, we propose a Multi-level Improved Simplified Swarm Optimization (MLiSSO) method which uses the improved simplified swarm optimization (iSSO) to the Multi-level Programming Problem (MLPP). It is applied to this pricing strategy model of the supply chain, and experiment with three related MLPPs in the past studies to verify the effectiveness of the method. The results show that the MLiSSO algorithm is effective, qualitative and stable, and can be used to solve the pricing strategy problem for supply chain models, furthermore, the algorithm can also be applied to other MLPPs.

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